The present invention relates to medical diagnostic ultrasonic imaging, and in particular to improved modes of SNR adaptive processing used in conjunction with such imaging.
Hwang U.S. Pat. No. 4,887,306 describes an adaptive temporal IIR filter where the coefficients of the filter are adaptive to the signal amplitude of the current and previous frames. Wright U.S. Pat. No. 5,595,179 describes another adaptive persistence processing for an ultrasound system where the IIR and FIR temporal filter coefficients are also adaptive to the signal amplitude of the current and previous frames. Uehara U.S. Pat. No. 5,495,846 describes a motion adaptive persistence processing where temporal filter coefficients are adaptive to the absolute difference of the current and previous frames.
Kim U.S. Pat. 5,653,234 No. discloses an ultrasonic imaging system that uses an SNR adaptive low-pass filter to process individual scan lines along the range dimension. In the disclosed embodiment the passband of the filter is reduced when the SNR decreases or the rate of change of the receive signal increases and increased when the SNR increases or the rate of change of the receive signal decreases. The rate of change of the receive signal is in one example computed from an estimate of the correlation distance in the receive signal.
Though the Kim patent discloses one specific application of SNR adaptive low-pass filtering along the range axis, the Kim patent does not suggest any application of SNR adaptive processing other than the single example described above. In particular, the Kim patent does not suggest the SNR adaptive processing modes described and claimed below.
By way of introduction, the preferred embodiments described below obtain a plurality of reference values which vary as a function of background noise at multiple locations within a frame. Background noise information is either acquired by imaging with the transmitters turned off, or estimated in real time by using the known differences in bandwidth and/or correlation lengths of the signal and noise, or modeled in real time using currently prevailing imaging parameters. Ultrasonic echo signals are compared with respective ones of these reference values and a processing function is selected in response to the comparison and applied to the ultrasonic echo signals.
One of the areas of application for SNR adaptive processing is in filtering. The coefficients of a spatial or temporal filter can be varied as a function of the SNR of the echo signals. SNR adaptive filters can be used to improve the SNR while preserving or improving the spatial and temporal resolution of the high-SNR signals. This can be achieved by low-pass filtering only the low-SNR signals or high-pass filtering only the high-SNR signals through an SNR adaptive spatial and/or temporal filter. Preferred SNR adaptive filters include but are not limited to pre-detection spatial whitening filters and post-detection spatial video filters or temporal persistence filters.
Another area of application for SNR adaptive processing is in synthesis. Synthesis is a term used for combining multiple images before amplitude detection for the purposes of increasing the spatial bandwidth and, thus, improving detail resolution and lesion detectability. Synthetic aperture and synthetic spectrum as described in U.S. Pat. Nos. 5,186,177 and 5,891,038, respectively, are two examples of synthesis. The performance of a synthesis function can be improved by making the combination ratio dependent on the SNR of the individual images. For synthetic aperture, for example, if the SNR of one of the images corresponding to one of the transmit/receive aperture combinations, and/or the ratio of the SNR of that image to the SNR of the other images is below a certain threshold, because of a partial blockage, for example, then the contribution of that image to the synthesis can be reduced or eliminated (and only) in the areas posterior to that blockage.
Another area of application for SNR adaptive processing is in compounding. Compounding is a term used for combining multiple images after amplitude detection to reduce speckle variance and, thus, improve lesion detectability. Frequency compounding, as disclosed for example in U.S. Pat. No. 5,961,460, and spatial compounding, as disclosed for example in U.S. patent application Ser. No. 09/199,945, are two examples of compounding. Both of these patent applications are assigned to the assignee of the present invention, and both are hereby incorporated by reference. The performance of a compounding function can also be improved by making the combination ratio dependent on the SNR of the individual images. For example, when compounding fundamental frequency and harmonic images, the contribution of the harmonic image can be reduced in those parts of the region of interest where the SNR of the harmonic image, and/or the ratio of the SNR of the harmonic image to that of the fundamental image, is below a certain threshold.
Various SNR adaptive processing functions can also be combined. For example, SNR adaptive spatial whitening can be used to maximize the spatial bandwidth of the component images before they are SNR adaptively synthesized or compounded.